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Heterosis-associated cellular and molecular processes were analyzed in seeds and seedlings of Arabidopsis thaliana accessions Col-0 and C24 and their heterotic hybrids. Microscopic examination revealed no advantages in terms of hybrid mature embryo organ sizes or cell numbers. Increased cotyledon sizes were detectable 4 days after sowing. Growth heterosis results from elevated cell sizes and numbers, and is well established at 10 days after sowing. The relative growth rates of hybrid seedlings were most enhanced between 3 and 4 days after sowing. Global metabolite profiling and targeted fatty acid analysis revealed maternal inheritance patterns for a large proportion of metabolites in the very early stages. During developmental progression, the distribution shifts to dominant, intermediate and heterotic patterns, with most changes occurring between 4 and 6 days after sowing. The highest incidence of heterotic patterns coincides with establishment of size differences at 4 days after sowing. In contrast, overall transcript patterns at 4, 6 and 10 days after sowing are characterized by intermediate to dominant patterns, with parental transcript levels showing the largest differences. Overall, the results suggest that, during early developmental stages, intermediate gene expression and higher metabolic activity in the hybrids compared to the parents lead to better resource efficiency, and therefore enhanced performance in the hybrids., (© 2012 The Authors. The Plant Journal © 2012 Blackwell Publishing Ltd.)

Natural genetic diversity provides a powerful resource to investigate how networks respond to multiple simultaneous changes. In this work, we profile maximum catalytic activities of 37 enzymes from central metabolism and generate a matrix to investigate species-wide connectivity between metabolites, enzymes, and biomass. Most enzyme activities change in a highly coordinated manner, especially those in the Calvin-Benson cycle. Metabolites show coordinated changes in defined sectors of metabolism. Little connectivity was observed between maximum enzyme activities and metabolites, even after applying multivariate analysis methods. Measurements of posttranscriptional regulation will be required to relate these two functional levels. Individual enzyme activities correlate only weakly with biomass. However, when they are used to estimate protein abundances, and the latter are summed and expressed as a fraction of total protein, a significant positive correlation to biomass is observed. The correlation is additive to that obtained between starch and biomass. Thus, biomass is predicted by two independent integrative metabolic biomarkers: preferential investment in photosynthetic machinery and optimization of carbon use.

Background: Natural accessions of Arabidopsis thaliana are characterized by a high level of phenotypic variation that can be used to investigate the extent and mode of selection on the primary metabolic traits. A collection of 54 A. thaliana natural accession-derived lines were subjected to deep genotyping through Single Feature Polymorphism (SFP) detection via genomic DNA hybridization to Arabidopsis Tiling 1.0 Arrays for the detection of selective sweeps, and identification of associations between sweep regions and growth-related metabolic traits., Results: A total of 1,072,557 high-quality SFPs were detected and indications for 3,943 deletions and 1,007 duplications were obtained. A significantly lower than expected SFP frequency was observed in protein-, rRNA-, and tRNA-coding regions and in non-repetitive intergenic regions, while pseudogenes, transposons, and non-coding RNA genes are enriched with SFPs. Gene families involved in plant defence or in signalling were identified as highly polymorphic, while several other families including transcription factors are depleted of SFPs. 198 significant associations between metabolic genes and 9 metabolic and growth-related phenotypic traits were detected with annotation hinting at the nature of the relationship. Five significant selective sweep regions were also detected of which one associated significantly with a metabolic trait., Conclusions: We generated a high density polymorphism map for 54 A. thaliana accessions that highlights the variability of resistance genes across geographic ranges and used it to identify selective sweeps and associations between metabolic genes and metabolic phenotypes. Several associations show a clear biological relationship, while many remain requiring further investigation.

Heterosis is a well-known phenomenon but the underlying molecular mechanisms are not yet established. To contribute to the understanding of heterosis at the molecular level, we analyzed genome-wide gene expression profile data of Arabidopsis thaliana in a systems biological approach. We used partial correlations to estimate the global interaction structure of regulatory networks. Our hypothesis states that heterosis comes with an increased number of partial correlations which we interpret as increased numbers of regulatory interactions leading to enlarged adaptability of the hybrids. This hypothesis is true for mid-parent heterosis for our dataset of gene expression in two homozygous parental lines and their reciprocal crosses. For the case of best-parent heterosis just one hybrid is significant regarding our hypothesis based on a resampling analysis. Summarizing, both metabolome and gene expression level of our illustrative dataset support our proposal of a systems biological approach towards a molecular basis of heterosis.

Rising demand for food and bioenergy makes it imperative to breed for increased crop yield. Vegetative plant growth could be driven by resource acquisition or developmental programs. Metabolite profiling in 94 Arabidopsis accessions revealed that biomass correlates negatively with many metabolites, especially starch. Starch accumulates in the light and is degraded at night to provide a sustained supply of carbon for growth. Multivariate analysis revealed that starch is an integrator of the overall metabolic response. We hypothesized that this reflects variation in a regulatory network that balances growth with the carbon supply. Transcript profiling in 21 accessions revealed coordinated changes of transcripts of more than 70 carbon-regulated genes and identified 2 genes (myo-inositol-1-phosphate synthase, a Kelch-domain protein) whose transcripts correlate with biomass. The impact of allelic variation at these 2 loci was shown by association mapping, identifying them as candidate lead genes with the potential to increase biomass production.

We propose a network structure-based model for heterosis, and investigate it relying on metabolite profiles from Arabidopsis. A simple feed-forward two-layer network model (the Steinbuch matrix) is used in our conceptual approach. It allows for directly relating structural network properties with biological function. Interpreting heterosis as increased adaptability, our model predicts that the biological networks involved show increasing connectivity of regulatory interactions. A detailed analysis of metabolite profile data reveals that the increasing-connectivity prediction is true for graphical Gaussian models in our data from early development. This mirrors properties of observed heterotic Arabidopsis phenotypes. Furthermore, the model predicts a limit for increasing hybrid vigor with increasing heterozygosity--a known phenomenon in the literature.

Two new large reciprocal sets of introgression lines (ILs) were created between the Arabidopsis accessions Col-0 and C24. In both sets (78 ILs with Col-0 background and 62 ILs with C24 background), the donor segments cover almost the entire genome with an average substitution size of 18.3 cM. In addition to the basic sets of ILs, further subILs were developed for 2 genomic regions allowing better mapping resolution. SubILs carrying donor segments with candidate genes for flowering time and reduced fertility were used to demonstrate the usefulness of the reciprocal ILs for quantitative trait loci detection and fine mapping. For subIL development at high resolution around the reduced fertility locus, we used modified CelI-based assays in one-well format for both marker development and genotyping. This serves as a very flexible and cost-effective approach.

Plant growth and development are tightly linked to primary metabolism and are subject to natural variation. In order to obtain an insight into the genetic factors controlling biomass and primary metabolism and to determine their relationships, two Arabidopsis thaliana populations [429 recombinant inbred lines (RIL) and 97 introgression lines (IL), derived from accessions Col-0 and C24] were analyzed with respect to biomass and metabolic composition using a mass spectrometry-based metabolic profiling approach. Six and 157 quantitative trait loci (QTL) were identified for biomass and metabolic content, respectively. Two biomass QTL coincide with significantly more metabolic QTL (mQTL) than statistically expected, supporting the notion that the metabolic profile and biomass accumulation of a plant are linked. On the same basis, three out the six biomass QTL can be simulated purely on the basis of metabolic composition. QTL based on analysis of the introgression lines were in substantial agreement with the RIL-based results: five of six biomass QTL and 55% of the mQTL found in the RIL population were also found in the IL population at a significance level of P < or = 0.05, with >80% agreement on the allele effects. Some of the differences could be attributed to epistatic interactions. Depending on the search conditions, metabolic pathway-derived candidate genes were found for 24-67% of all tested mQTL in the database AraCyc 3.5. This dataset thus provides a comprehensive basis for the detection of functionally relevant variation in known genes with metabolic function and for identification of genes with hitherto unknown roles in the control of metabolism.

D-ribulose-1,5-bisphosphate carboxylase/oxygenase (Rubisco) catalyses the first step in photosynthetic carbon assimilation and represents the largest sink for nitrogen in plants. Improvement of its kinetic properties or the efficiency with which it is used in planta would benefit photosynthesis, nitrogen and water use efficiency, and yield. This paper presents a new non-radioactive microplate-based assay, which determines the product [3-phosphoglycerate (3-PGA)] in an enzymic cycle between glycerol-3-phosphate dehydrogenase and glycerol-3-phosphate oxidase. High sensitivity permits use of highly diluted extracts, and a short reaction time to avoid problems due to fall-off. Throughput was several hundreds of samples per person per day. Sensitivity and convenience compared favourably with radioisotopic assays, which were previously used to assay Rubisco. Its use is illustrated in three applications. (1) Maximal and initial activities and the K(m) for ribulose-1,5-bisphosphate were determined in raw extracts of leaves from several species. Similar values were obtained from those in the literature. (2) Diurnal changes were compared in rosettes of wild-type (WT) Arabidopsis and the starchless pgm mutant. Despite these dramatic differences in carbon metabolism, Rubisco activity and activation were similar in both genotypes. (3) A preliminary association mapping study was performed with 118 Arabidopsis accessions, using 183 markers that probably cover approximately 3-8% of the total genome. At a P-value < 0.005, two, two and no quantitative trait loci (QTL) were found for Rubisco maximal activity, initial activity and activation state, respectively. Inspection of the genomic regions that span these markers revealed these QTL involved genes not previously implicated in the regulation of Rubisco expression or activity.

The decline of available fossil fuel reserves has triggered world-wide efforts to develop alternative energy sources based on plant biomass. Detailed knowledge of the relations of metabolism and biomass accumulation can be expected to yield powerful novel tools to accelerate and enhance energy plant breeding programs. We used metabolic profiling in the model Arabidopsis to study the relation between biomass and metabolic composition using a recombinant inbred line (RIL) population. A highly significant canonical correlation (0.73) was observed, revealing a close link between biomass and a specific combination of metabolites. Dividing the entire data set into training and test sets resulted in a median correlation between predicted and true biomass of 0.58. The demonstrated high predictive power of metabolic composition for biomass features this composite measure as an excellent biomarker and opens new opportunities to enhance plant breeding specifically in the context of renewable resources.

A new large set of reciprocal recombinant inbred lines (RILs) was created between the Arabidopsis accessions Col-0 and C24 for quantitative trait mapping approaches, consisting of 209 Col-0 x C24 and 214 C24 x Col-0 F(7 )RI lines. Genotyping was performed using 110 evenly distributed framework single nucleotide polymorphism markers, yielding a genetic map of 425.70 cM, with an average interval of 3.87 cM. Segregation distortion (SD) was observed in several genomic regions during the construction of the genetic map. Linkage disequilibrium analysis revealed an association between a distorted region at the bottom of chromosome V and a non-distorted region on chromosome IV. A detailed analysis of the RILs for these two regions showed that an SD occurred when homozygous Col-0 alleles on chromosome IV coincided with homozygous C24 alleles at the bottom of chromosome V. Using nearly isogenic lines segregating for the distorted region we confirmed that this genotypic composition leads to reduced fertility and fitness.

Quantitative trait loci (QTL) analysis was used to identify genes underlying natural variation in primary cell wall composition in Arabidopsis (Arabidopsis thaliana). The cell walls of dark-grown seedlings of a Bay-0 x Shahdara recombinant inbred line population were analyzed using three miniaturized global cell wall fingerprinting techniques: monosaccharide composition analysis by gas chromatography, xyloglucan oligosaccharide mass profiling, and whole-wall Fourier-transform infrared microspectroscopy. Heritable variation and transgression were observed for the arabinose-rhamnose ratio, xyloglucan side-chain composition (including O-acetylation levels), and absorbance for a subset of Fourier-transform infrared wavenumbers. In total, 33 QTL, corresponding to at least 11 different loci controlling dark-grown hypocotyl length, pectin composition, and levels of xyloglucan fucosylation and O-acetylation, were identified. One major QTL, accounting for 51% of the variation in the arabinose-rhamnose ratio, affected the number of arabinan side chains presumably attached to the pectic polysaccharide rhamnogalacturonan I, paving the way to positional cloning of the first gene underlying natural variation in pectin structure. Several QTL were found to be colocalized, which may have implications for the regulation of xyloglucan metabolism. These results demonstrate the feasibility of combining fingerprinting techniques, natural variation, and quantitative genetics to gain original insight into the molecular mechanisms underlying the structure and metabolism of cell wall polysaccharides.